Technology and technology-related information can be thought of as “diffusing” through the community of potential adopters. This community consists of entities (e.g. individuals and organizations) and multi-faceted relationships between entities. For an individual, this diffusion may have several stages such as “I’ve heard of it,” “my friends like it,” “maybe it will solve my problem,” and “I’ve bought it.” For organizations, especially in the DoD/Government acquisition community, the stages of diffusion and adoption are different and more complicated (probably). Adopter communities can be modeled as social networks. This topic seeks to explore how knowledge about potential adopter communities and diffusion within them can help understand and improve the process of technology adoption. Questions include:

• How can we best model adopter communities as social networks?• What kinds of information flows over these networks? Using what processes and protocols?• Can analysis tools be developed? To do what? (e.g. find bottlenecks)• How can information about the technology be best crafted, perhaps at different points in the adoption cycle or for different parts of the network?• Does narrative story-telling help and if so, how and where?• How can we instrument or get information about these dynamic networks and how they evolve?

Possible student project topics:

• Survey existing social network models and explore their applicability to adopter communities• The role of Web 2.0 technologies in information and technology diffusion• Develop techniques for measuring dynamic social networks and corresponding analysis tools

2. How do we measure success at technology adoption?

Faculty lead: Dan Nussbaum (Operations Research) and Nick Dew (Graduate School of Business and Public Policy)

Not all technology is worthy of transition, and adoption of technology in a sub-community or larger community is never all-or-none. Adoption is a complex process that evolves over time, and some technology (e.g. telephones) finds wide-spread adoption while other technology (e.g. 3D chat over PCs) have failed to achieve the same level of adoption. Adoption in a DoD/DARPA context has its own complexities that lead to other difficulties with definition and measurement. This topic seeks to develop approaches and metrics for measuring technology adoption. Questions include:

• How is “success” defined? What definitions are applicable to what kinds of technologies and contexts?• What kinds of general metrics are appropriate?• How do we take measurements, and where?

Possible student project topics:

• Benchmark a variety of DARPA programs using the database of MOAs and PCRs already collected• Design an adoption measurement framework and database

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